Ontology highlight
ABSTRACT:
PROVIDER: PRJNA817719 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18360436_1.fastq.gz | Fastqsanger.gz | |||
| SRR18360436_2.fastq.gz | Fastqsanger.gz | |||
| SRR18360437_1.fastq.gz | Fastqsanger.gz | |||
| SRR18360437_2.fastq.gz | Fastqsanger.gz | |||
| SRR18360438_1.fastq.gz | Fastqsanger.gz |
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Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities
2009-06-01 | GSE13977 | GEO
Project description:Soil microbial community is a complex blackbox that requires a multi-conceptual approach (Hultman et al., 2015; Bastida et al., 2016). Most methods focus on evaluating total microbial community and fail to determine its active fraction (Blagodatskaya & Kuzyakov 2013). This issue has ecological consequences since the behavior of the active community is more important (or even essential) and can be different to that of the total community. The sensitivity of the active microbial community can be considered as a biological mechanism that regulates the functional responses of soil against direct (i.e. forest management) and indirect (i.e. climate change) human-induced alterations. Indeed, it has been highglihted that the diversity of the active community (analyzed by metaproteomics) is more connected to soil functionality than the that of the total community (analyzed by 16S rRNA gene and ITS sequencing) (Bastida et al., 2016). Recently, the increasing application of soil metaproteomics is providing unprecedented, in-depth characterisation of the composition and functionality of active microbial communities and overall, allowing deeper insights into terrestrial microbial ecology (Chourey et al., 2012; Bastida et al., 2015, 2016; Keiblinger et al., 2016). Here, we predict the responsiveness of the soil microbial community to forest management in a climate change scenario. Particularly, we aim: i) to evaluate the impacts of 6-years of induced drought on the diversity, biomass and activity of the microbial community in a semiarid forest ecocosystem; and ii) to discriminate if forest management (thinning) influences the resistance of the microbial community against induced drought. Furthermore, we aim to ascertain if the functional diversity of each phylum is a trait that can be used to predict changes in microbial abundance and ecosystem functioning.
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Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+–N and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics.
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Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities We used lignin degradation as a model process to demonstrate the use of an oligonucleotide microarray for directly detecting gene expression in soil communities using signal amplification instead of template amplification to avoid the introduction of PCR bias. In the current study, we analyzed mRNA isolated from two distinct soil microbial communities and demonstrate our ability to detect the expression of a small subset of lignin degrading genes following exposure to a lignitic substrate. We also included purified control amplicons and mixed target experiments with pure P. chrysosporium genomic cDNA to determine the level of interference from soil biomass on target hybridization.
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Project description:Tibet is one of the most threatened regions by climate warming, thus understanding how its microbial communities function may be of high importance for predicting microbial responses to climate changes. Here, we report a study to profile soil microbial structural genes, which infers functional roles of microbial communities, along four sites/elevations of a Tibetan mountainous grassland, aiming to explore potential microbial responses to climate changes via a strategy of space-for-time substitution. Using a microarray-based metagenomics tool named GeoChip 4.0, we showed that microbial communities were distinct for most but not all of the sites. Substantial variations were apparent in stress, N and C cycling genes, but they were in line with the functional roles of these genes. Cold shock genes were more abundant at higher elevations. Also, gdh converting ammonium into urea was more abundant at higher elevations while ureC converting urea into ammonium was less abundant, which was consistent with soil ammonium contents. Significant correlations were observed between N-cycling genes (ureC, gdh and amoA) and nitrous oxide flux, suggesting that they contributed to community metabolism. Lastly, we found by CCA, Mantel tests and the similarity tests that soil pH, temperature, NH4+M-bM-^@M-^SN and vegetation diversity accounted for the majority (81.4%) of microbial community variations, suggesting that these four attributes were major factors affecting soil microbial communities. Based on these observations, we predict that climate changes in the Tibetan grasslands are very likely to change soil microbial community functional structure, with particular impacts on microbial N cycling genes and consequently microbe-mediated soil N dynamics. Twelve samples were collected from four elevations (3200, 3400, 3600 and 3800 m) along a Tibetan grassland; Three replicates in every elevation
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